Robustness in motion averaging

Abstract

The averaging of multiple pairwise relative motions in a sequence provides a fast and accurate method of camera motion estimation with a wide range of applications, including view registration, robotic path estimation, super-resolution. Since this approach involves averaging in the Lie-algebra of the underlying motion representation, it is non-robust and susceptible to contamination due to outliers in the individual relative motions. In this paper, we introduce a graph-based sampling scheme that efficiently remove such motion outliers. The resulting global motion solution is robust and also provides an empirical estimate of the inherent statistical uncertainty. Example results are provided to demonstrate the efficacy of our approach to incorporating robustness in motion averaging. © Springer-Verlag Berlin Heidelberg 2006.